SOURCE-LINKED INTELLIGENCE
New Horizons in Glass Structure Prediction and Mechanics
ed approaches for the design of new glass compositions and microstructures with improved fracture resistance. This requires the development of computational approaches, from ab initio calculations to artificial intelligence, to integrate structural descriptors and glass chemistry with advanced processing and mechanical properties into holistic tools. NewGLASS challenges the current glass design strategies in order to create such tools. For this purpose, an interdisciplinary approach is proposed, in which structural descriptors at the short- and medium-range length scales are first identified and quantified based on emergent statistical mechanics and persistent homology techniques. Guided by these results, high-throughput simulations at various length scales are combined with machine learning algorithms to design novel glass compositions, tailored deformation mechanisms, and 3D-printed microstructures to achieve superior fracture resistance. By having experiments and modelling complement and advance each other reciprocally, NewGLASS will find order in disorder and provide the scienti
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- recordType
- award
- status
- SIGNED
- region
- EU
- value
- 1996935
- unit
- EUR
Evidence & attribution
European Commission, CORDIS Horizon Europe project dataset. Metadata adapted.
License: CORDIS reuse policy
First collected: 2026-09-20T00:21:03.701Z. This is not the publication date.